This disclosure relates to a system and method of correcting a particulate matter sensor signal for soot deposit stochastic variation in the form of large particle strikes, blow-offs, and periodic delaminations.
Rich combustion conditions, such as those which occur in diffusion flame processes that are present in diesel engines and other internal combustion engines, produce particulate matter, which is carried in its exhaust stream. Particulate matter emissions are typically limited by emissions regulations and it is common for modern diesel engines to be equipped with a particulate filter. As part of the emissions regulations, diagnosis of the particulate filter is mandated and the use of a particulate matter sensor is one such diagnostic system. Thus, it is desirable to accurately measure particulate matter real-time in vehicles to ensure that the engine and particulate filter are operating in compliance with government regulations. It is also desirable to measure particulate matter using emissions testing equipment during engine development on a dynamometer, for example.
One type of particulate matter sensor includes electrodes that are closely spaced on an electrically non-conductive substrate. As particulate matter accumulates between the electrodes, the sensor's electric resistance decreases as the initially non-conductive substrate surface between electrodes becomes gradually more electrically conductive due to the deposited soot, which is indicative of the amount of particulate matter in the sensed exhaust pipe, either directly produced by the combustion process or its remnants escaping the action of the particulate filter.
Experimentally observed step-like unusual changes in the measured particulate matter deposit resistance are commonly attributed to either occasional bombardment of the sensor surface with particles much larger than the typical size within the particles' size distribution, or losses of already-deposited particle mass due to blow-offs. This dramatic alteration of particulate matter resistance gradient measured in the time domain corrupts the particulate matter assessment algorithms which may be based on the measure of the cycle time, i.e., time markers representing arbitrarily selected sensor resistances indicating the start of sensing cycle and its end. These error effects are explained in, for example, “Sensing of Particulate Matter for On-Board Diagnosis of Particulate Filters”, H. Husted et al, SAE Int. J. Engines 5(2) (2012).
There is a need to account for the contribution of large particle strikes and/or blow-offs, which corrupt the signal and provide an inaccurate particulate matter reading.